Special Issue "Image Processing Using FPGAs 2021"

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Image and Video Processing".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editor

Prof. Dr. Donald Bailey
E-Mail Website
Guest Editor
Department of Mechanical and Electrical Engineering, School of Food and Advanced Technology, Massey University, Palmerston North, 4442, New Zealand
Interests: machine vision; FPGA based design; digital image processing
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Field Programmable Gate Arrays (FPGAs) are increasingly being used for the implementation of image processing applications. This is especially the case for real-time embedded applications where latency and power are important considerations. An FPGA embedded in a smart camera is able to perform much of the image processing directly as the image is streamed from the sensor, providing a processed data stream, rather than images. Modern system-on-chip (SoC) FPGAs allow the design for an application to be appropriately partitioned between hardware and software to exploit the characteristics of both platforms.

Simply porting a software algorithm onto an FPGA often gives disappointing results, because many image processing algorithms have been optimised for a serial processor. It is usually necessary to transform the algorithm to efficiently exploit the parallelism and resources available on an FPGA. This can lead to novel algorithms and hardware computational architectures, both at the image processing operation level and also the application level.

The aim of this Special Issue is to present and highlight novel algorithms, architectures, techniques and applications of FPGAs in the domain of image processing. Each submission should clearly evidence the novel contributions in one or more of these areas or provide a comprehensive review of some aspect of image processing on FPGAs.

Prof. Dr. Donald Bailey
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Hardware algorithms for imaging
  • Computational imaging architectures
  • Reconfigurable image processing systems
  • Parallel image processing
  • Hardware acceleration for imaging applications
  • FPGA based smart cameras
  • FPGA based deep learning

Published Papers (1 paper)

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Research

Article
iDocChip: A Configurable Hardware Accelerator for an End-to-End Historical Document Image Processing
J. Imaging 2021, 7(9), 175; https://doi.org/10.3390/jimaging7090175 - 03 Sep 2021
Viewed by 213
Abstract
In recent years, there has been an increasing demand to digitize and electronically access historical records. Optical character recognition (OCR) is typically applied to scanned historical archives to transcribe them from document images into machine-readable texts. Many libraries offer special stationary equipment for [...] Read more.
In recent years, there has been an increasing demand to digitize and electronically access historical records. Optical character recognition (OCR) is typically applied to scanned historical archives to transcribe them from document images into machine-readable texts. Many libraries offer special stationary equipment for scanning historical documents. However, to digitize these records without removing them from where they are archived, portable devices that combine scanning and OCR capabilities are required. An existing end-to-end OCR software called anyOCR achieves high recognition accuracy for historical documents. However, it is unsuitable for portable devices, as it exhibits high computational complexity resulting in long runtime and high power consumption. Therefore, we have designed and implemented a configurable hardware-software programmable SoC called iDocChip that makes use of anyOCR techniques to achieve high accuracy. As a low-power and energy-efficient system with real-time capabilities, the iDocChip delivers the required portability. In this paper, we present the hybrid CPU-FPGA architecture of iDocChip along with the optimized software implementations of the anyOCR. We demonstrate our results on multiple platforms with respect to runtime and power consumption. The iDocChip system outperforms the existing anyOCR by 44× while achieving 2201× higher energy efficiency and a 3.8% increase in recognition accuracy. Full article
(This article belongs to the Special Issue Image Processing Using FPGAs 2021)
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